Research On The Optimization Of GPS Integrity Monitoring Technology In The Final Approach Phase

The rapid development of the Global Navigation Satellite System(GNSS)has made it possible for modern civil aircraft to use GPS and other satellite navigation systems to determine their position and speed,and to use them globally,which is unmatched by traditional navigation equipment.The advent of GNSS has greatly improved the accuracy of aircraft navigation,but civil aviation has higher requirements for navigation accuracy and integrity,and the final approach phase is the riskiest part of the aircraft approach procedure,so it is important to ensure the reliability of the navigation system during the final approach phase.The use of on-board equipment to enhance the performance of satellite navigation systems is by far the easiest way to achieve this,so this thesis investigates the optimization of the accuracy and integrity of the navigation system during the final approach phase of flight.Firstly,the importance of accuracy and integrity of navigation systems in ensuring flight safety during the final approach phase is explained,and the need for their optimization is illustrated.By introducing the basic concepts of accuracy and integrity and the basic algorithms involved in both,the shortcomings in traditional algorithms are analysed and studied,including the least squares residual method,the parity vector method and the method of four-star positioning solution.Secondly,aiming at the problems existing in the height measurement of barometric altimeter and GPS,a data fusion algorithm of barometric altimeter /GPS combined system is proposed,by establishing a combined system measurement model,fusing the combined system data based on the great likelihood estimation,and obtaining a constant Kalman gain filtering algorithm based on the Kalman filter principle,while considering the changes of sea level pressure and temperature,and changing the Kalman gain by adding adaptive weights to realize the correction of the combined system observation results to improve the altitude accuracy in the final approach phase.Then,to address the problem that the receiver autonomous integrity monitoring(RAIM)algorithm is not available when the number of visible satellites is small,an AAIM algorithm based on multiple solution separation is proposed by introducing aircraft barometric altimeter data as external data according to the characteristics of the aircraft autonomous integrity monitoring(AAIM)algorithm.By using the data information of GNSS and barometric altimeter,a combined observation model is established,and the recursive least squares method and the iterative optimization of the weight matrix are used to compromise between position accuracy and integrity in order to obtain the optimal solution of the vertical protection threshold,which ensures the integrity of the navigation system during the final approach phase.Finally,a simulation platform is designed and constructed to study and analysis the effectiveness and feasibility of the proposed algorithm.The simulation results show that the standard deviation of the altitude error of the adaptive Kalman filtering algorithm used in this thesis is 7.27 m in the case of constant sea level pressure and temperature,and 12.92 m in the case of varying sea level pressure and temperature,which significantly improves the altitude estimation accuracy in the case of incorrect barometric altimeter measurements;the optimal VPL value obtained by the AAIM optimization algorithm is 15.5m less than that before the optimization The optimal VPL value obtained by the AAIM optimization algorithm is reduced by 43.5m compared with that before the optimization,which is equivalent to 59.26% of the traditional RAIM algorithm.With five visible satellites,the algorithm can still achieve the function of detecting and eliminating faulty satellites,effectively ensuring satellite integrity monitoring under poor observation conditions.